Triple

T18308378
Position Surface form Disambiguated ID Type / Status
Subject Kirovsky District E438549 entity
Predicate containsUrbanTypeSettlement P11388 FINISHED
Object Pavlovo NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Pavlovo | Statement: [Kirovsky District, containsUrbanTypeSettlement, Pavlovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pavlovo
Context triple: [Kirovsky District, containsUrbanTypeSettlement, Pavlovo]
  • A. Pavlovo
    Pavlovo is a historic town in Russia, known as an administrative center and for its traditional metalworking and handicraft industries.
  • B. Pavlovo chosen
    Pavlovo is an urban-type settlement located within the Kirovsky District of Leningrad Oblast in northwestern Russia.
  • C. Lyudinovo
    Lyudinovo is an industrial town in western Russia known for its engineering and manufacturing sectors.
  • D. Karlovo
    Karlovo is a historic town in central Bulgaria, known as the birthplace of national hero Vasil Levski and as a gateway to the Balkan Mountains.
  • E. Nova Pazova
    Nova Pazova is a town in northern Serbia known as a suburban and industrial settlement within the municipality of Stara Pazova in the Vojvodina region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50215e0c48190a4679d432b6ee596 completed April 19, 2026, 4:25 p.m.
Created at: April 10, 2026, 10:35 a.m.